LiteLLM will show you the normalized, provider-agnostic version of your request. This is useful for debugging, learning, and understanding how LiteLLM handles different providers and options.

LiteLLM maps exceptions across all supported providers to the OpenAI exceptions. All our exceptions inherit from OpenAI's exception types, so any error-handling you have for that, should work out of the …

Setting API Keys, Base, Version LiteLLM allows you to specify the following: API Key API Base API Version API Type Project Location Token Useful Helper functions: check_valid_key() …

LiteLLM supports all AI models from CometAPI. CometAPI provides access to 500+ AI models through a unified API interface, including cutting-edge models like GPT-5, Claude Opus 4.1, and various other …

Getting started with the AI/ML API is simple. Follow these steps to set up your integration: 1. Get Your API Key To begin, you need an API key. You can obtain yours here: 🔑 Get Your API Key 2. Explore …

We recommend using litellm.responses() / Responses API for the latest OpenAI models (GPT-5, gpt-5-codex, o3-mini, etc.)

LiteLLM allows you to call non-Responses API models via a bridge to LiteLLM's /chat/completions endpoint. This is useful for calling Anthropic, Gemini and even non-Responses API OpenAI models.

LiteLLM can automatically convert OpenAPI specifications into MCP servers, allowing you to expose any REST API as MCP tools. This is useful when you have existing APIs with OpenAPI/Swagger …

import litellm # First, create a response response = litellm.responses( model="openai/o1-pro", input="Tell me a three sentence bedtime story about a unicorn.", max_output_tokens=100 ) # Get …

Quick Start - LiteLLM Proxy CLI Run the following command to start the litellm proxy